AI-Guided Payment Terminal Location for Visually Impaired Users
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Solution Overview
Problem
Visually impaired individuals face difficulty in locating payment terminals for transactions due to the absence of human assistance in stores and kiosks.
Innovation Solution
A system and method using a mobile device's camera or sensor to identify payment terminals and provide haptic or auditory feedback to guide users to the terminal, potentially confirming the transaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a mobile device uses camera or sensor to identify payment terminal, then visually impaired users can locate payment terminal independently, but the device complexity increases
Solution Approach 1:
The mobile device is designed to perform multiple functions: it serves as both a standard communication device and an accessibility tool with camera-based payment terminal detection, haptic feedback guidance, and transaction confirmation capabilities. This multi-functionality allows visually impaired users to locate and complete transactions independently without requiring separate specialized devices.
Solution Approach 2:
The system introduces an intermediary AI model that acts as a mediator between the camera/sensor input and the user. The AI model processes environmental data, identifies payment terminals, and translates this information into haptic feedback patterns that guide the user, thereby managing system complexity through intelligent abstraction.
2Measurement precision
If the mobile device provides active guidance with haptic or auditory feedback, then the user can be guided to payment terminal accurately, but the energy consumption increases
Solution Approach 1:
The haptic feedback system operates periodically rather than continuously, providing tactile cues at key moments during the approach to the payment terminal. The mobile device alternates between active sensing/feedback modes and lower-power states, reducing overall energy consumption while maintaining guidance accuracy when needed.
Solution Approach 2:
The system replaces continuous auditory feedback (which would require constant audio processing and output) with haptic feedback mechanisms that can be activated intermittently. Haptic engines consume less energy when activated periodically compared to continuous audio output, thereby reducing overall energy consumption while maintaining measurement precision.
3Measurement precision
If the system uses AI model to identify payment terminal from environmental data, then identification accuracy improves, but the processing time increases
Solution Approach 1:
The AI model is pre-trained on extensive datasets of payment terminal appearances, symbols, and configurations before deployment. This preliminary training allows the model to rapidly recognize and identify payment terminals in real-world scenarios without requiring extensive processing time during actual use, thus improving identification accuracy while minimizing time loss.
Solution Approach 2:
The system processes environmental data selectively rather than analyzing every possible feature. The AI model focuses on key identifying features such as payment terminal symbols, shapes, and distinctive visual characteristics, performing partial analysis that achieves sufficient identification accuracy without the computational overhead of exhaustive processing.
4Ease of operation
If the mobile device continuously senses environmental data to guide user, then the user can be actively guided to payment terminal, but the battery life decreases
Solution Approach 1:
The environmental sensing and feedback systems operate in periodic cycles rather than continuously. The mobile device alternates between active sensing phases (capturing camera/sensor data and providing haptic feedback) and idle phases (reducing sensor activity and feedback output), thereby maintaining active guidance capability while extending battery life through reduced continuous operation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables visually impaired users to locate and complete payment transactions independently by actively guiding them to the payment terminal and confirming the transaction.
Implementation Method 1
A camera on a smart phone of the user may capture visual data of a merchant environment
Implementation Method 2
The user may be actively guided to the payment terminal by the smart phone providing feedback to the user of the position of the smart phone relative to the payment terminal
Implementation Method 3
The payment transaction may be initiated once the mobile device is within a near-field communication range of the payment terminal
Data Source
AI summary
A system and method for assisting a user to locate a payment terminal and execute a payment transaction. Video or other environmental data is captured with a camera or other sensor on a phone, card, or other mobile device and examined to identify the terminal. The user is actively guided to the terminal via haptics, sound, or other feedback mechanisms indicating whether the device is moving closer to or farther from the terminal. The user may be similarly guided specifically to a tap-to-pay area on the terminal for payment. The transaction is initiated once the device moves into close proximity with or touches the tap-to-pay area. Artificial intelligence may be trained to recognize different types of terminals and used to identify the particular terminal and guide the user to it. Confirmation of the transaction by the user may be provided to an issuer prior to the issuer authorizing payment.